Cybernetics: A Definition (Pangaro)

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CYBERNETICS: A Definition

[In 1990 Heinz von Foerster was approached by Macmillan to compose an entry fortheir 1991 Macmillan Encyclopedia of Computers. Von Foerster recommended themto me and I composed the following text and incorporated a figure that I had createdfor an earlier purpose. My original text follows, which was published in a slightly re-edited form. Final text is Copyright (c) Macmillan Publishing.]

Artificial Intelligence and cybernetics: Aren't they the same thing? Or, isn't one aboutcomputers and the other about robots? The answer to these questions is emphatically,No.

Artificial Intelligence (AI) uses computer technology to strive toward the goal ofmachine intelligence and considers implementation as the most important result;cybernetics uses epistemology (the limits to how we know what we know) tounderstand the constraints of any medium (technological, biological, or social) andconsiders powerful descriptions as the most important result.

The field of AI came into being when the concept of universal computation [Minsky1967], the cultural view of the brain as a computer, and the availability of digitalcomputing machines were combined. The field of cybernetics came into being whenconcepts of information, feedback, and control [Wiener 1948] were generalized from

specific applications (e.g. in engineering) to systems in general, including systems ofliving organisms, abstract intelligent processes and language.

Origins of "cybernetics"

The term itself originated in 1947 when Norbert Wiener used it to name a disciplineapart from, but touching upon, such established disciplines as electrical engineering,mathematics, biology, neurophysiology, anthropology, and psychology. Wiener,Arturo Rosenblueth and Julian Bigelow needed a new word to refer to their newconcept, and they adapted a Greek word meaning "steersman" to invoke the richinteraction of goals, predictions, actions, feedback and response in systems of all

kinds (the term "governor" derives from the same root) [Wiener 1948]. Earlyapplications in the control of physical systems (aiming artillery, designing electricalcircuits and maneuvering simple robots) clarified the fundamental roles of theseconcepts in engineering; but the relevance to social systems and the softer scienceswas also clear from the start. Many researchers from the 1940s through 1960 workedsolidly within the tradition of cybernetics without necessarily using the term, somelikely (R. Buckminster Fuller) but many less obviously (Gregory Bateson, MargaretMead).

Limits to knowing

In working to abstract concepts common to all systems, early cybernetic researchersquickly realized that "the science of observed systems" cannot be divorced from "thescience of observing systems" [von Foerster 1974] --- because it is we who observe.The cybernetic approach is centrally concerned with this unavoidable limit of what

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we can know: our own subjectivity. In this way cybernetics is aptly called "appliedepistemology". At minimum, its utility is the production of useful descriptions, and,specifically, descriptions that include the observer in the description. Cyberneticdescriptions of psychology, language, arts, performance, or intelligence (to name afew) may be quite different from more conventional, hard "scientific" views ---although cybernetics can be rigorous too. Implementation may then follow in

software and/or hardware, or in the design of social, managerial and other classes ofinterpersonal systems.

Origins of AI in cybernetics

Ironically but logically, AI and cybernetics have each gone in and out of fashion andinfluence in the search for machine intelligence. Cybernetics started in advance of AI,but AI has dominated for the last 25 years. Now recent difficulties in AI have led torenewed search for solutions that mirror the past approaches of cybernetics. WarrenMcCulloch and Walter Pitts were the first to propose a synthesis of neurophysiologyand logic that tied the capabilities of brains to the limits of Turing computability

[McCulloch & Pitts 1965]. The euphoria that followed spawned the field of AI[Lettvin 1989] along with early work on computation in neural nets, or, as thencalled, perceptrons. However the fashion of symbolic computing rose to squelchperceptron research. Only when discontent slowly grew over repeated failures toachieve machine intelligence by symbolic means within AI did interest in neuralnetworks rise again in the late 1980s. However this is not to say that current fashionin neural nets is a return to where cybernetics has been. Much of the modern work inneural nets rests in the philosophical tradition of AI and not that of cybernetics.

Philosophy of cybernetics

AI is predicated on the presumption that knowledge is a commodity that can be storedinside of a machine, and that the application of such stored knowledge to the realworld constitutes intelligence [Minsky 1968]. Only within such a "realist" view of theworld can, for example, semantic networks and rule-based expert systems appear tobe a route to intelligent machines. Cybernetics in contrast has evolved from a"constructivist" view of the world [von Glasersfeld 1987] where objectivity derivesfrom shared agreement about meaning, and where information (or intelligence forthat matter) is an attribute of an interaction rather than a commodity stored in acomputer [Winograd & Flores 1986]. These differences are not merely semantic incharacter, but rather determine fundamentally the source and direction of researchperformed from a cybernetic, versus an AI, stance.




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Figure 1. Underlying philosophical differences between AI and cybernetics aredisplayed by showing how they each understand the terms in the central column. Forexample, the concept of "representation" is cast quite differently in the two fields.Relations on the left are causal arrows and reflect the reductionist reasoning inherentin AI's "realist" perspective of the world-as-it-is. Relations on the right are non-

hierarchical and circular and reflect a "constructivist" perspective, where the world isinvented by an intelligence acting in a social tradition, rather than discovered.

Influences

Winograd and Flores credit the influence of Humberto Maturana, a biologist whorecasts the concepts of "language" and "living system" with a cybernetic eye[Maturana & Varela 1988], in shifting their opinions away from the AI perspective.They quote Maturana: "Learning is not a process of accumulation of representationsof the environment; it is a continuous process of transformation of behavior throughcontinuous change in the capacity of the nervous system to synthesize it. Recall does

not depend on the indefinite retention of a structural invariant that represents an entity(an idea, image or symbol), but on the functional ability of the system to create, whencertain recurrent demands are given, a behavior that satisfies the recurrent demands orthat the observer would class as a reenacting of a previous one." [Maturana 1980]Cybernetics has directly affected software development in intelligent training,knowledge representation, cognitive modeling, computer supported cooperativework, and neural modeling. Useful results have been demonstrated in all these areas.Like AI, however, cybernetics has not produced recognizable solutions to themachine intelligence problem, or at least has not for domains considered complex inthe metrics of symbolic processing. Many beguiling artifacts have been producedwith an appeal more familiar in an entertainment medium or to organic life than a

piece of software [Pask 1971]. Meantime, in a repetition of history in the 1950s, theinfluence of cybernetics is being felt throughout the hard and soft sciences, as well asin AI. This time however it is its epistemological stance, rather than its abstraction ofthe concepts of information, feedback, and purpose, that is its contribution to thesefields.

Bibliography

Lettvin, Jerome Y., "Introduction to Volume 1" in W S McCulloch., Volume 1, ed.,Rook McCulloch, Salinas, California: Intersystems Publications, 1989, 7-20.

McCulloch, Warren S. and Walter H. Pitts, "A Logical Calculus of the IdeasImmanent in Nervous Activity", inEmbodiments of Mindby Warren S. McCulloch.Cambridge, Massachusetts: The MIT Press, 1965, 19-39.

Maturana, Humberto R., Biology of Cognition, 1970. Reprinted in Maturana,Humberto R. and Francisco Varela,Autopoiesis and Cognition: The Realization ofthe Living. Dordrecht: Reidel, 1980, 2-62.

Maturana, Humberto R. and Francisco J. Varela, The Tree of Knowledge. Boston andLondon: New Science Library, Shambala Publications, Inc, 1988.

Minksy, Marvin, Computation: Finite and Infinite Machines. New Jersey:PrenticeHall, Inc., 1967.

Minsky, Marvin, ed., Semantic Information Processing. Cambridge, Massachusetts:




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The MIT Press, 1968.

Pask, Gordon, "A Comment, a Case History and a Plan". In Cybernetic Serendipity,ed, J. Reichardt. Rapp and Carroll, 1970. Reprinted in Cybernetics, Art and Ideas,ed., J. Reichardt. London: Studio Vista, 1971, 76-99.

von Foerster, Heinz, ed., Cybernetics of Cybernetics. Sponsored by a grant from thePoint Foundation to the Biological Computer Laboratory, University of Illinois,Urbana, Illinois, 1974. [Now again available in re-published form from ???]

von Glasersfeld, Ernst, The Construction of Knowledge, Contributions to ConceptualSemantics. Seaside, California: Intersystems Publications, 1987.

Wiener, Norbert, Cybernetics, or control and communication in the animal and themachine. Cambridge, Massachusetts: The Technology Press; New York: John Wiley& Sons, Inc., 1948.

Winograd, Terry and Fernando Flores, Understanding Computers And Cognition: A

New Foundation for Design. Norwood, New Jersey: Ablex Publishing Corporation,1986.

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Cybernetics: A Definition (Pangaro)